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20 Ways to Track Fraud with Data Analytics


Has your business experienced problems with fraud? If so, you’re not alone—and if no, it’s possible that you just haven’t looked hard enough.

A 2020 study from PricewaterhouseCoopers found that 47% of businesses had at least one incidence of fraud in the previous two years, with an average of six instances per company. Customer fraud was the most common, followed by cybercrime, asset misappropriation, and bribery and corruption. The incidents were nearly evenly split between internal and external perpetrators, with 20% of cases including a collusion between inside and outside parties. Altogether, the losses for the 5,000+ businesses surveyed amounted to $42 billion.

With the destabilizing nature of the COVID-19 pandemic, the likelihood of fraud is even more prevalent. A report from the Association of Certified Fraud Examiners (ACFE) found that 77% of companies surveyed as of August 2020 experienced an increase in fraudulent activity since the start of the pandemic, with 92% expecting fraud to increase over the next 12 months.

Companies are rushing to fast-track onboarding of new vendors, sometimes without proper vetting. And with many businesses flying blind in their newfound remote work environments, it can be easy to overlook the financial checks and balances that might occur in the corporate office. But if you’re not looking closely, it can be easy to miss situations where your ledger doesn’t balance out correctly.

Fortunately, data analytics can spot warning signs that humans sometimes miss. Here’s a look at some key types of data inconsistencies you can use to spot fraud from both insider and outsider forces.

General ledger entries

Ledger entries should be scrutinized closely for potential fraud or errors. For instance:

1. Identify and search for suspicious keywords.

Identify suspicious journal entry descriptions using keywords that may indicate unauthorized or invalid entries.

2. Stratify general ledger accounts.

Look at the normal range of values to spotlight entries outside of that range—if your average ledger entry for payroll is $2M and one shows up as $500K, the entry may warrant further scrutiny.

3. Hunt for outlier journal entry amounts.

Use your analytics solution to flag entries that are more than two standard deviations away from typical entries, as that may point to an accounting error or potential fraud.

Business expenses

Expenses in areas such as travel and entertainment are often where unscrupulous employees may fudge numbers through multiple methods. Here are a few ways to monitor for fraud in expense tracking:

4. Analyze the average spend by department.

Your sales department likely has much higher travel costs than your programming team. Monitor department spending over time to understand the average range for each division and set up an alert to trigger if the department deviates from that range. In some cases, a specific seasonal event, like a conference, may throw off the balance, so be sure to do a line-by-line analysis to confirm whether everything is on track.

5. Check for suspicious reimbursement claims.

One common area where employees may (often inadvertently) double-dip is around fuel and mileage reimbursement. If they’re already submitting mileage for reimbursement, fuel charges should be flagged as a duplicate item.

6. Identify split purchases.

Employees may skirt around purchase limits by breaking one large purchase into two different line items—your analytics solution can alert you to such “split purchases.”

7. Watch for high group dining expenses.

Historical records should give you a good baseline level for average group dining expenses. If a record is out of normal range, it should be flagged for review.

8. Find round amounts.

See an expense for a round amount, like a $200 charge? These charges aren’t likely to happen by chance, so it may mean that the employee is using their company card to take out cash advances.

9. Identify duplicate claims.

Some employees may submit expense reports for purchases they’ve already charged to their corporate accounts, getting reimbursed twice for the same expense.

10. Deactivate dormant company cards.

If an employee leaves your company but their card is still active, it may be susceptible to fraudulent use. Make sure these credit cards are shut down immediately.


11. Flag suspicious salary increases.

Keep an eye out for multiple, small salary increases for the same employee within a single calendar year, and contact HR to verify they are approved.

12. Identify phantom employees still on the payroll.

Are employees who’ve been terminated or quit still showing up on the payroll? In some cases, this may mean that another employee has modified the payroll to their own bank account details as a way to conduct financial fraud.

Vendor payments

Contractor payments are rife for fraudulent behavior, as either the vendor or an unscrupulous employee can funnel money through fake or inflated invoices. Here are a few tips for avoiding vendor fraud and billing oversights:

13. Segregate vendor creation and billing.

Ensure that the employee responsible for creating vendor profiles isn’t also responsible for generating and approving invoices. A dishonest employee can take advantage of this role to generate fake invoices from fictitious vendors, as can an outsider who’s gotten access to system credentials.

14. Flag duplicate invoices.

Vendors may submit the same invoice multiple times, either by accident or as a way to follow up on unpaid bills. If you don’t have a system for tracking and flagging duplicates, you may end up paying the same invoice twice.

15. Watch for frequent changes to vendor details.

For example, if a master table includes frequent changes to a vendor address, this is a potential indicator for fraud.

16. Identify matches between vendor and employee details in your master table.

If you identify matching bank details, address, or other data between a vendor file and employee payroll details, this may be an indicator that the employee has set up a fraudulent vendor account.

17. Find non-PO purchases above the dollar limit.

At most companies, purchases above a certain threshold should be associated with a purchase order—if you notice large purchases that aren’t, they may be indicative of fraud or an accounting or vendor error.

18. Track blanket receipts.

Blanket receipts refer to invoices for multiple services that haven’t yet been rendered. Make sure that, if vendors are issuing payment in advance of service or receipt of goods, you have a way to track the delivery of their work.


Fraud and accounting errors can also cause problems when working with your customers. Here are a couple of ways to verify accurate accounting with your customers:

19. Validate customer credit limits.

Make sure that all your customers have consistent credit limits in line with their business credit profile and company size, flagging those that have outsize credit limits. Those customers may not be able to pay back outstanding loans.

20. Identify sanctioned customers.

Run your customer accounts through a database that will flag sanctioned customers from public records, including OFAC’s SDN list, the SAM list, HHS’s LEIE list, and others. This will help you identify customers who may need further validation or those who should be cut off.

There are many ways to identify fraud and accounting errors within your business, but if you’re only reviewing transactions manually, you’re likely to miss a lot. Errors, unauthorized charges, and signs of fraud can slip past your Accounts Payable team’s eyes, potentially leading to millions of dollars of losses over the course of a year.

In order to accurately detect and quickly remediate fraud before it has a major impact on your organization, it’s important to implement best-in-class analytics that can analyze 100% of your financial data (instead of sample testing) to automatically identify red flags.

Your tool set should integrate with both internal and external datasets, including your ERP, payroll system, and government datasets such as census data and other public records that can be used to verify your data’s accuracy. A continuous delivery system, which will instantly provide you with alerts regarding potential violations, can also use custom rules and triggers that are designed for your industry. By deploying advanced machine learning, your accounting, compliance, and IT teams will have strong intelligence available to help them keep your organization secure.


Detecting & preventing fraud with data analytics

This eBook covers:

  • Key considerations for implementing a successful fraud program.
  • The most effective data analysis techniques for detecting and preventing fraud.
  • Practical analytics tests you can implement right now across different business areas.

Download eBook

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